In typical PET imaging, a radiopharmaceutical agent is introduced into an object to be imaged via injection, inhalation, or ingestion. After administration of the radiopharmaceutical, the physical and bio-molecular properties of the agent cause it to concentrate at specific locations in the human body. The actual spatial distribution of the agent, the intensity of the region of accumulation of the agent, and the kinetics of the process from administration to its eventual elimination are all factors that may have clinical significance. During this process, a positron emitter attached to the radiopharmaceutical agent will emit positrons according to the physical properties of the isotope, such as half-life, branching ratio, etc.
The radionuclide emits positrons, and when an emitted positron collides with an electron, an annihilation event occurs, wherein the positron and electron are combined. Most of the time, an annihilation event produces two gamma rays (at 511 keV) traveling at substantially 180 degrees apart.
By detecting the two gamma rays, and drawing a line between their locations, i.e., the line-of-response (LOR), one can determine the likely location of the original disintegration. While this process will only identify a line of possible interaction, by accumulating a large number of those lines, and through a tomographic reconstruction process, the original distribution can be estimated. In addition to the location of the two scintillation events, if accurate timing (within few hundred picoseconds) is available, a time-of-flight (TOF) calculation can add more information regarding the likely position of the event along the line. Limitations in the timing resolution of the scanner will determine the accuracy of the positioning along this line. Limitations in the determination of the location of the original scintillation events will determine the ultimate spatial resolution of the scanner, while the specific characteristics of the isotope (e.g., energy of the positron) will also contribute (via positron range and co-linearity of the two gamma rays) to the determination of the spatial resolution the specific agent.
The collection of a large number of events creates the necessary information for an image of an object to be estimated through tomographic reconstruction. Two detected events occurring at substantially the same time at corresponding detector elements form a line-of-response that can be histogrammed according to their geometric attributes to define projections, or sinograms to be reconstructed. Events can also be added to the image individually.
The fundamental element of the data collection and image reconstruction is therefore the LOR, which is the line traversing the system-patient aperture. Additional information can be obtained regarding the location of the event. First, it is known that, through sampling and reconstruction, the ability of the system to reconstruct or position a point is not space-invariant across the field of view, but is better in the center, slowly degrading toward the periphery. A point-spread-function (PSF) is typically used to characterize this behavior. Tools have been developed to incorporate the PSF into the reconstruction process. Second, the time-of-flight, or time differential between the arrival of the gamma ray on each detector involved in the detection of the pair, can be used to determine where along the LOR the event is more likely to have occurred.
The above described detection process must be repeated for a large number of annihilation events. While each imaging case must be analyzed to determine how many counts (i.e., paired events) are required to support the imaging task, current practice dictates that a typical 100-cm long, FDG (fluoro-deoxyglucose) study will need to accumulate several hundred million counts. The time required to accumulate this number of counts is determined by the injected dose of the agent and the sensitivity and counting capacity of the scanner.
PET imaging systems use detectors positioned across from one another to detect the gamma rays emitting from the object. Typically a ring of detectors is used in order to detect gamma rays coming from each angle. Thus, a PET scanner is typically substantially cylindrical to be able to capture as much radiation as possible, which should be, by definition, isotropic. The use of partial rings and rotation of the detector to capture missing angles is also possible, but these approaches have severe consequences for the overall sensitivity of the scanner. In a cylindrical geometry, in which all gamma rays included in a plane have a chance to interact with the detector, an increase in the axial dimension has a very beneficial effect on the sensitivity or ability to capture the radiation. Thus, the best design is that of a sphere, in which all gamma rays have the opportunity to be detected. Of course, for application to humans, the spherical design would have to be very large and thus very expensive. Accordingly, a cylindrical geometry, with the axial extent of the detector being a variable, is realistically the starting point of the design of a modern PET scanner.
Once the overall geometry of the PET scanner is known, another challenge is to arrange as much scintillating material as possible in the gamma ray paths to stop and convert as many gamma rays as possible into light. In order to be able to reconstruct the spatio-temporal distribution of the radio-isotope via tomographic reconstruction principles, each detected event will need to be characterized for its energy (i.e., amount of light generated), its location, and its timing. Most modern PET scanners are composed of several thousand individual crystals, which are arranged in modules and are used to identify the position of the scintillation event. Typically scintillator elements have a cross section of roughly 4 mm×4 mm. Smaller or larger dimensions and non-square sections are also possible. The length or depth of the crystal will determine how likely the gamma ray will be captured, and typically ranges from 10 to 30 mm. One example of a scintillation crystal is LYSO (or Lu1.8Y0.2SiO5:Ce or Lutetium Orthosilicate), which is chosen for its high light output, fast rise time, fast decay time, high average atomic number, and high density. Other crystals can be used.
PET imaging relies on the conversion of gamma rays into light through fast and bright scintillation crystals. After determining the interaction position in the scintillator and time pairing of individual events, the location of the annihilation process can be recreated. These actions require very fast components—detector and electronics—and they also require excellent signal to noise ratio. With high quality electronics, the signal to noise ratio is mainly determined by the inherent Poisson statistics involved in the detection process. Detecting more photons will result in improved signal-to-noise-ratio, and, therefore, better spatial and timing resolution. No improvement in detector design and electronics can compensate for significant loss of light in the detection process. The fraction of the total amount of light collected (relative to the amount created in the scintillator) is a good measure of the efficiency of the design. So to maximize the amount of light collected, one would try to get the light sensor as close as possible to the scintillation crystal and avoid reflections and other edge effects. This would then force the arrangement to be large array detector with short distance between crystal and sensor.
As described above, a PET imaging system is more than just a counter and, in addition to detecting the presence of a scintillation event, the system must identify its location. By properly documenting how light is being distributed to the multiple light sensors, it is possible to assign an event location for any given set of sensor responses. Light therefore needs to be distributed to multiple sensors.
Coordinates for the x-position and the y-position of a scintillation event are calculated using Anger arithmetic, wherein the x- and y-positions are determined by taking the ratios between the responses of neighboring sensors. Estimating positions from linear combinations of sensor signals leads to distortions, such as pincushion-like distortions. For crystal arrays the decoding of the crystal in which an interaction occurred is generally accomplished through the use of a lookup table generated from a flood map, with the distortions often making it difficult to unambiguously identify crystals in the corners or along edges, as can be seen in FIG. 2A.
FIG. 2A shows a drawing of a flood map, where the dots show the centroid of the detected light for each scintillator element in a module. When the centroids cluster together in the corners, the wings of the centroids statistical distributions overlap, creating ambiguity in the crystal decoding. This ambiguity in the crystal decoding ultimately limits the resolution of the PET imaging system. Poor crystal decoding degrades the PET imaging system performance by increasing the probability that a scintillation event will be assigned to the wrong scintillator element. The incorrect assignment of scintillation events to the wrong scintillator elements not only degrades spatial resolution, but it also degrades energy and timing resolution because different timing and energy corrections are applied to different scintillator elements. To improve crystal decoding the light sharing among the photosensors must be carefully controlled for each scintillator element, especially those in the edge regions.